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Record W2141448606 · doi:10.1109/mwsym.2003.1212568

Efficient computation of thin-layer structures with the unconditionally stable ADI-FDTD method

2003· article· en· W2141448606 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsDalhousie University
FundersNational Science Council
KeywordsFinite-difference time-domain methodComputationDielectricComputer scienceComputational electromagneticsStability (learning theory)Electrical impedanceMicrostripElectromagneticsComputational scienceElectronic engineeringAlgorithmMaterials scienceElectromagnetic fieldOpticsPhysicsEngineeringElectrical engineeringOptoelectronics

Abstract

fetched live from OpenAlex

Efficient computation is a key consideration in computational electromagnetics, especially for complex VLSI structures that contain thin dielectric layers or electrically small objects. Due to the CFL stability condition, it is very inefficient to apply the conventional FDTD method to thin-layer structures because fine mesh (and therefore small time step) is required. In this paper, the unconditionally stable ADI-FDTD method is employed to circumvent the difficulty. With applications in computing effective dielectric constant (/spl epsiv//sub eff/) and characteristic impedance (Z/sub 0/) of cylindrical microstrip lines, it is shown that the computation time with the ADI-FDTD method is much shorter than that of the conventional FDTD method without sacrificing modeling accuracy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.642
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.276
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it